seo-drift

To monitor SEO regressions, you can capture a baseline snapshot of critical on-page elements and compare it against a post-deployment fetch. The skill runs 17 rule-based comparisons with severity levels to detect silent changes to title tags, canonicals, and structured data.

SEO drift refers to silent changes in critical on-page elements that cause ranking and CTR losses over time. Detecting it involves hashing HTML and JSON-LD schema, then comparing current page states against a known-good baseline snapshot to identify regressions.

Yes, you can track Core Web Vitals and schema changes for any trackable URL. The skill captures HTTP status, heading structure, Open Graph tags, and JSON-LD schema, storing comparison results locally in SQLite for historical review and traffic drop investigations.

To check if a canonical change impacted SEO, fetch the page safely through the pipeline and run a deterministic comparison against the stored baseline. The diffing engine flags canonical changes with specific severity classifications like CRITICAL or WARNING.

Automating regression monitoring for structured data requires capturing content hashes and JSON-LD schema in an initial baseline. By running subsequent page fetches through the comparison pipeline, you generate an HTML report highlighting exact schema changes before they cost rankings.

No external databases are needed. The skill stores baseline snapshots, page element hashes, and comparison results locally in a SQLite database, allowing you to review historical SEO drift and generate HTML reports without external dependencies.